Lesson 4B.3.3
4B.3.3 Testing the product moment correlation coefficient Quiz: Pearson Edexcel Further Maths, Unit 20
20 questions
In partnership with Revision Ninja
Lesson 4B.3.3, Testing the product moment correlation coefficient: 20 multiple choice questions for the Pearson Edexcel Further Maths (9FM0), Unit 20: Non-parametric tests, written with Revision Ninja.
Host it live on the board and students join with a game code on their own devices, or revise alone with Free Play. The answers are revealed in the game.
The 20 questions
-
Which null hypothesis is used to test whether a product moment correlation coefficient is zero?
- H0: sample r = 1
- H0: rho = 0
- H0: mu_x = mu_y
- H0: rho = 1
-
Under what condition are the critical values for the product moment correlation coefficient valid?
- Both variables must be discrete
- The sample size must be at least 300
- The data must first be converted to ranks
- The data come from a population with a bivariate normal distribution
-
For the test statistic t = r sqrt(n - 2) / sqrt(1 - r^2), what are the degrees of freedom?
- n - 2
- n
- n + 2
- n - 1
-
Which test is suitable for testing correlation when the data are not believed to be bivariate normal?
- The product moment correlation test using t critical values
- Spearman's rank correlation test
- The chi-squared test of a population variance
- The paired t-test on the raw values
-
What happens to the product moment correlation r if a constant is added to every value of x?
- r is multiplied by that constant
- r is unchanged
- r increases by that constant
- r changes sign
-
A researcher expects a positive correlation and tests for it. Which alternative hypothesis is appropriate?
- H1: rho < 0
- H1: rho not equal to 0
- H1: rho = 0
- H1: rho > 0
-
In a hypothesis test for correlation, the p-value is less than the significance level. What is the correct conclusion?
- Reject H0, and conclude there is evidence of a non-zero correlation
- Accept H0 and conclude that rho is exactly zero
- Prove that the population correlation equals the sample r
- Conclude the data are bivariate normal
-
A sample of n = 12 pairs has r = 0.6. What is the test statistic t, to 2 decimal places?
- 3.46
- 1.58
- 0.60
- 2.37
-
Using the test statistic from a sample of n = 12 with r = 0.6, what is the conclusion at the 5% two-tailed level? (Critical value with 10 df is 2.228.)
- The test cannot be carried out because n is too small
- Reject H0, since r is greater than 0.5
- Reject H0, since 2.37 exceeds 2.228
- Accept H0, since 2.37 is less than 2.228
-
A sample of n = 20 pairs has r = 0.3. Is this significant at the 5% one-tailed level? (Critical value with 18 df is 1.734.)
- Yes, since t = 1.33 exceeds 1.734
- No, because samples must have at least 30 pairs
- No, t = 1.33 is below the critical value 1.734
- Yes, since r = 0.3 is positive
-
A sample of n = 10 pairs has r = -0.7. What is the test statistic t, to 2 decimal places?
- 2.77
- -0.91
- -1.98
- -2.77
-
A sample of n = 17 pairs has r = 0.45. What is the test statistic t, to 2 decimal places?
- 1.74
- 0.45
- 1.95
- 2.13
-
A sample of n = 8 pairs has r = 0.8. What is the test statistic t, to 2 decimal places?
- 2.45
- 4.80
- 1.33
- 3.27
-
A sample of n = 6 pairs has r = 0.9. Is H0 rejected at the 1% two-tailed level? (Critical value with 4 df is 4.604.)
- Yes, since t = 4.13 exceeds 2.776
- No, since t = 4.13 is below 4.604
- No, because n must be at least 10
- Yes, since r = 0.9 is above 0.5
-
A sample of n = 27 pairs has r = 0.4. What is the test statistic t, to 2 decimal places?
- 1.09
- 2.06
- 0.40
- 2.18
-
Why must the bivariate normal assumption hold for the product moment correlation test?
- Normality guarantees that the mean equals the median for both variables
- The critical values are derived from the distribution of r under bivariate normality, which the t-based test relies on
- It guarantees that r equals 1 for large samples
- It ensures the sample is random within each subgroup
-
A researcher has r = 0.45 from n = 12 pairs and tests H1: rho > 0 at the 5% level. (One-tailed critical value with 10 df is 1.812.) What is the conclusion?
- Significant, because one-tailed tests are always more powerful
- Not significant, since t = 1.59 is below 1.812
- Not significant, because n must be at least 30
- Significant, since r = 0.45 is above 0.4
-
A sample of pairs gives a large r but includes one extreme outlier. Why can the product moment test mislead?
- Outliers affect only the means, not the value of r
- One outlier can inflate or deflate r, and it can break the bivariate normal assumption behind the test
- Outliers increase the degrees of freedom of the test
- Outliers always increase r, so the test is always significant
-
A test gives t = 3.0 with 8 degrees of freedom. Two-tailed critical values are 2.306 (5%) and 3.355 (1%). What is the conclusion?
- Not significant at either level
- Significant at the 5% level but not at the 1% level
- Significant at the 1% level but not at the 5% level
- Significant at both the 5% and 1% levels
-
For the same sample correlation r = 0.3, which sample size gives the larger test statistic t?
- The statistic depends only on the sign of r
- Both give the same t
- n = 100
- n = 20
Related quizzes
- Spearman's rank correlation coefficient Quiz · 4B.3.1-4B.3.2 · 20 questions
- Proof by mathematical induction Quiz · 1.1 · 20 questions
- Quadratic equations and complex arithmetic Quiz · 2.1-2.2 · 20 questions
- Matrix arithmetic and inverses Quiz · 3.1-3.2 · 20 questions
- Expectation of discrete random variables Quiz · 3B.1.1 · 20 questions
- The Poisson distribution Quiz · 3B.2.1 · 20 questions
- Geometric and negative binomial models Quiz · 3B.3.1 · 20 questions
- Hypothesis tests for the Poisson distribution Quiz · 3B.4.1 · 20 questions
- Applying the Central Limit Theorem Quiz · 3B.5.1 · 20 questions
- Goodness of fit tests for discrete distributions Quiz · 3B.6.1 · 20 questions